VinDr | AI solutions for medical imaging
Time 2022-09-10 15:33:25Web Name: VinDr | AI solutions for medical imaging
WebSite: http://www.vindr.ai
ID:310710
Keywords:
solutions,AI,VinDr,imagingDescription:
Shaping the future of medical data analysis
The Smart Health Center at VinBigdata aims to build the VinDr ecosystem that revolutionizes the storage, processing, analysis, and understanding of medical data.
Request DemoVinDr CAD
VinDr CAD is a platform for medical image analysis that consists of multiple Computer-Aided Diagnosis (CAD) tools to assist doctors in making fast and precise diagnoses. The platform can be seamlessly integrated into any Picture Archiving and Communication System (PACS) without breaking standard clinical workflows. Each CAD tool can automatically suggest diagnosis and localize a certain number of abnormalities based on appropriate DICOM images in a real-time fashion. Focusing on some of the most common imaging modalities, VinDr CAD currently offers 7 following tools.
VinDr-ChestXR
VinDr-ChestXR is a CAD tool for chest X-ray interpretation. It is able to identify 6 lung diseases and localize 22 types of common abnormalities on chest X-ray.
The system has been trained and validated on half a million chest X-ray studies from both public sources and several hospitals in Vietnam. The bounding box annotation and disease labeling for our private dataset have been performed by top Vietnamese radiologists. The accuracy of the system is above 90% for almost all diseases and findings.
Request DemoVinDr-SpineXR
VinDr-SpineXR is a CAD tool for spine x-ray interpretation. It is able to classify a spine X-ray scan as normal and abnormal. The system can also localize 6 types of common abnormalities on the image.
VinDr-SpineXR has been trained and validated on a large-scale dataset of approximately 10 000 studies collected from several hospitals in Vietnam, in which the bounding box annotation and disease labeling have been performed by top Vietnamese radiologists. The accuracy for the abnormality detection is about 60% in terms of mAP@0.2.
Request DemoVinDr-Mammo
VinDr-Mammo is a CAD tool for mammography interpretation. It is able to classify a mammography study into 3 BI-RADS (Breast Imaging-Reporting and Data System) levels and 4 types of breast density. The system can also localize 13 types of common abnormalities on mammography.
VinDr-Mammo has been trained and validated on about 50,000 studies collected from several hospitals in Vietnam. The bounding box annotation and disease labeling for this private dataset have been performed by top Vietnamese radiologists. The accuracy for BI-RADS classification is above 80%.
Request DemoVinDr-ChestCT
VinDr-ChestCT is a CAD tool for Chest CT interpretation. It is able to identify 6 thoracic diseases and localize 24 types of common abnormalities on Chest CT scans.
The system will be trained and validated on about 30,000 studies collected from both public sources and several hospitals in Vietnam. The bounding box annotation (on 3-D volumes) and disease labeling for our private dataset have been performed by top Vietnamese radiologists.
Request DemoVinDr-LiverCT
VinDr-LiverCT is a CAD tool for abdomen CT interpretation. It is able to identify 10 liver diseases, including different types of liver cancer, and localize 24 types of common liver abnormalities on abdomen CT scans.
The system will be trained and validated on about 10,000 studies collected from both public sources and several hospitals in Vietnam. The bounding box annotation (on 3-D volumes) and disease labeling for our private dataset have been performed by top Vietnamese radiologists.
Request DemoVinDr-BrainCT
VinDr-BrainCT is a CAD tool for brain CT interpretation. It is able to identify 9 brain diseases, including several types of stroke, and localize 17 types of common abnormalities on brain CT scans.
The system will be trained and validated on about 30,000 studies collected from both public sources and several hospitals in Vietnam. The bounding box annotation (on 3-D volumes) and disease labeling for our private dataset have been performed by top Vietnamese radiologists.
Request DemoVinDr-BrainMR
VinDr-BrainMRis a CAD toolfor brain MRI interpretation. It is able to identify 9 brain diseases, including brain tumor, and localize 20 types of common abnormalities on brain MRI scans.
The system will be trained and validated on about 3,000 studies collected from both public sources and several hospitals in Vietnam. The bounding box annotation (on 3-D volumes) and disease labeling for our private dataset have been performed by top Vietnamese radiologists.
Request DemoResearch
We are passionate about applying computer vision (CV), machine learning (ML) and deep learning (DL) models to build computed-aided detection (CADe) and computer aided diagnosis (CADx) systems from very large-scale clinical datasets of multiple imaging modalities (X-ray, CT, MRI, etc). Our research includes new methods and ML/DL models for radiologist-level understanding and interpretation from medical images. We aim to validate and publish our work on top-tier journals and conferences.
A novel multi-view deep learning approach for BI-RADS and density assessment of mammograms
Huyen T. X. Nguyen, Sam B. Tran, Dung B. Nguyen, Hieu H. Pham, and Ha Q. Nguyen – IEEE International Engineering in Medicine and Biology Conference (EMBC 2022), accepted.
Phase Recognition in Contrast-Enhanced CT Scans based on Deep Learning and Random Sampling
Binh T. Dao, Thang V. Nguyen, Hieu H. Pham, and Ha Q. Nguyen – Medical Physics, 2022.
VinDr-Mammo: A large-scale benchmark dataset for computer-aided diagnosis in full-field digital mammography
VinDr-PCXR: An open, large-scale chest radiograph dataset for interpretation of common thoracic diseases in children
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Learning from multiple expert annotators for enhancing anomaly detection in medical Image analysis
Khiem H. Le, Tuan V. Tran, Hieu H. Pham, Hieu T. Nguyen, Tung T. Le,
An Accurate and Explainable Deep Learning System Improves Interobserver Agreement in the Interpretation of Chest Radiograph
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VinDr-SpineXR: A deep learning framework for spinal lesions detection and classification from radiographs
Hieu T. Nguyen, Hieu H. Pham, Nghia T. Nguyen, Ha Q. Nguyen, Thang Q. Huynh, Minh Dao, Van Vu – International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI 2021).
Learning to Automatically Diagnose Multiple Diseases in Pediatric Chest Radiographs Using Deep Convolutional Neural Networks
Thanh T. Tran, Hieu H. Pham, Thang V. Nguyen, Tung T. Le, Hieu T. Nguyen, Ha Q. Nguyen – IEEE/CVF International Conference on Computer Vision Workshops (ICCV Workshop 2021)
DICOM Imaging Router: An Open Deep Learning Framework for Classification of Body Parts from DICOM X-ray Scans
Hieu H. Pham, Dung V. Do, Ha Q. Nguyen – IEEE/CVF International Conference on Computer Vision Workshops (ICCV Workshop 2021)
VinDr-RibCXR: A Benchmark Dataset for Automatic Segmentation and Labeling of Individual Ribs on Chest X-rays
Hoang C. Nguyen, Tung T. Le, Hieu H. Pham, Ha Q. Nguyen – International Conference on Medical Imaging with Deep Learning (MIDL 2021).
Enhancing MRI Brain Tumor Segmentation with an Additional Classification Network
Hieu T. Nguyen, Tung T. Le, Thang V. Nguyen and Nhan T. Nguyen–The 6th International Workshop on Brain Lesions 2020, MICCAI 2020, Peru, October (2020).
VinDr-CXR: An open dataset of chest X-rays with radiologist’s annotations
Ha Q. Nguyen, Khanh Lam, Linh T. Le, Hieu H. Pham, Dat Q. Tran, Dung B. Nguyen, Dung D. Le, Chi M. Pham, Hang T. T. Tong, Diep H. Dinh, Cuong D. Do, Luu T. Doan, Cuong N. Nguyen, Binh T. Nguyen, Que V. Nguyen, Au D. Hoang, Hien N. Phan, Anh T. Nguyen, Phuong H. Ho, Dat T. Ngo, Nghia T. Nguyen, Nhan T. Nguyen, Minh Dao, Van Vu – arXiv preprint.
Deep learning for detection and segmentation of artefact and disease instances in gastrointestinal endoscopy
Sharib Ali, Mariia Dmitrieva, Noha Ghatwary, Sophia Bano, Gorkem Polat, Alptekin Temizel, Adrian Krenzer, Amar Hekalo, Yun Bo Guo, Bogdan Matuszewski, Mourad Gridach, Irina Voiculescu, Vishnusai Yoganand, Arnav Chavan, Aryan Raj, Nhan T. Nguyen, Dat Q. Tran, Le Duy Huynh, Nicolas Boutry, Shahadate Rezvy, Haijian Chen, Yoon Ho Choi, Anand Subramanian, Velmurugan Balasubramanian, Xiaohong W. Gao, Hongyu Hu, Yusheng Liao, Danail Stoyanov, Christian Daul, Stefano Realdon, Renato Cannizzaro, Dominique Lamarque, Terry Tran-Nguyen, Adam Bailey, Barbara Braden, James East, Jens Rittscher – Medical Image Analysis Volume 70, May 2021.
A clinical validation of VinDr-CXR, an AI system for detecting abnormal chest radiographs
Ngoc Huy Nguyen, Ha Quy Nguyen, Nghia Trung Nguyen, Thang Viet Nguyen, Hieu Huy Pham, Tuan Ngoc-Minh Nguyen – arXiv preprint.
Interpreting chest X-rays via CNNs that exploit disease dependencies and uncertainty labels
Hieu H. Pham, Tung T. Le, Dat Q. Tran, Dat T. Ngo, Ha Q. Nguyen – Neurocomputing (IF: 4.434), Volume 437, 21 May 2021, Pages 186-194.
Interpreting chest X-rays via CNNs that exploit disease dependencies and uncertainty labels
Hieu H. Pham, Tung T. Le, Dat Q. Tran, Dat T. Ngo, Ha Q. Nguyen – Short paper, Proceedings of Medical Imaging with Deep Learning (MIDL 2020).
Detection and segmentation of endoscopic artefacts and disease using deep architectures
Nhan T. Nguyen, Dat Q. Tran, Dung B. Nguyen – IEEE International Symposium on Biomedical Imaging (ISBI 2020).
A CNN-LSTM Architecture for Detection of Intracranial Hemorrhage on CT scans
Nhan T. Nguyen, Dat Q. Tran, Nghia T. Nguyen, Ha Q. Nguyen – Short paper, Proceedings of Medical Imaging with Deep Learning (MIDL 2020).
Our Team
Ha Nguyen
Ph.D. UIUC, M.Sc. MIT, Postdoc EPFL
DirectorDung Nguyen
B.Sc. HUST, Kaggle Grand Master
Data Team LeadNghia Nguyen
B.Sc. UET
VinDr Lab Team LeadDan Vu
B.Sc. FTU
VinDr CAD Team LeadPhuc Truong
B.Sc. LQDTU
VinDr PACS Team LeadThang Nguyen
B.Sc. UET
AI Research EngineerHieu Pham
B.Sc. HUST
Software EngineerTu Vu
B.Sc. HUST
Software EngineerHieu Nguyen
B.Sc. HUST
AI Research EngineerTung Le
B.Sc. UET
AI Research EngineerNews
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Read MoreContact Us
Smart Health Center – VinBigData JSC
Address: 9th floor, Century Tower, Times City, 458 Minh Khai, Hai Ba Trung, Ha Noi
Email: vindr.contact@vinbigdata.org
TAGS:solutions AI VinDr imaging
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